(a) Field of the Invention
The present invention relates a method of selecting a candidate vector and a method of detecting a transmission symbol. More particularly, the present invention relates to a method of selecting a candidate vector and a method of detecting a transmission symbol in a multiple input multiple output (MIMO) system using spatial multiplexing (SM).
(b) Description of the Related Art
In recent years, a mobile communication system has been required to provide a high-speed data service including images and packets, in addition to an existing sound service. In order to satisfy these requirements, a multiple input multiple output (MIMO) system using spatial multiplexing (SM) that enables multiplex data layer transmission has attracted attention.
In the MIMO system using spatial multiplexing, a data layer indicating different information is transmitted through each transmitting antenna, and a receiving terminal separates the transmitted data layers. In the data layer separation method according to the related art, maximum likelihood (ML) bit metric detection has been used in which a maximum likelihood metric is calculated for each of transmission symbol vectors that can be combined and a transmission symbol vector having the smallest ML metric is searched, in order to perform optimal transmission symbol detection.
However, even though the ML bit metric detection provides optimal transmission symbol detection performance, since hardware complexity is exponentially increased with respect to the size of a constellation and the number of transmitting antennas, the ML bit metric detection has a drawback in that extremely high complexity is required.
In order to remedy the drawback in the ML bit metric detection, as linear signal detection having reduced complexity, a zero forcing (ZF) method and a minimum mean square estimator (MMSE) method have been suggested in the related art. However, these methods have a problem in that performance is degraded as compared with the ML bit metric detection. In order to remedy the drawback in the ML bit metric detection, as non-linear signal detection having reduced complexity, ordered successive interference cancellation (OSIC) that is known as vertical Bell Lab layered space time (VBLAST) has been suggested. However, while the VBLAST can be easily implemented and provides excellent performance than the ZF and MMSE methods, it has a problem in that performance is degraded as compared with the ML bit metric detection.
As methods that have been suggested in the related art, there are original maximum likelihood detection with QR decomposition and M-algorithm (original QRM-MLD), and QRM-MLD with ranking. However, in the original QRM-MLD, excellent transmission symbol detection performance is provided, but complexity is high. In the QRM-MLD with ranking, complexity is reduced, but transmission symbol detection performance is degraded as compared with the original QRM-MLD.
The above information disclosed in this Background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.